A QoS-Aware Multi-Criteria Routing Approach Based on Grey Wolf Optimization Algorithm in Internet of Things Networks

The Internet of Things (IoT) is an information architecture based on the Internet that fosters interaction between goods and services in a secure and reliable environment. Several critical challenges exist in the IoT ecosystem, including security, scalability, availability, interoperability, performance, and big data analytics. Among these, routing remains a fundamental challenge in IoT environments. Various routing approaches have been proposed by researchers, each with its own advantages and limitations. To address some of these limitations, the present study proposes a multi-criteria QoS-aware routing approach using Grey Wolf Optimization (GWO) in IoT networks. Evaluation metrics for the proposed method include waiting time, packet loss rate, CPU utilization rate, network usage time, resource utilization rate, and response time. The evaluation results indicate that the proposed approach outperforms comparable methods in terms of reducing waiting time and packet loss. Additionally, the network lifetime achieved by the proposed method is superior to that of the compared approaches. Furthermore, analysis of CPU and resource usage confirms the higher efficiency of the proposed method. The experimental results demonstrate that the proposed method is better than other methods.